Real-Time Video Object Detection and Filtering for Privacy
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Solution Overview
Problem
Current visual communication technologies fail to effectively modify video content of physical environments in real-time based on user preferences and contexts, leading to potential privacy issues and suboptimal communication experiences across different locations and settings.
Innovation Solution
A method and system that determine and apply configuration settings using machine learning to modify video content by detecting and filtering out irrelevant or sensitive objects, adjusting video quality, and optimizing workspace environments for various contexts, allowing seamless video communication across different hardware and locations while prioritizing user privacy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video content of physical environment is transmitted in real-time, then communication quality is improved, but privacy issues arise due to exposure of sensitive objects
Solution Approach 1:
The system extracts and identifies sensitive objects from the video content using object detection technology, then selectively removes or obscures only those specific objects while transmitting the rest of the video content. This allows real-time video transmission to maintain communication quality while protecting privacy by taking out only the harmful elements (sensitive objects) from the video stream.
Solution Approach 2:
The system applies different processing qualities to different regions of the video content. Sensitive objects detected in the video are subjected to obscuration or removal, while non-sensitive areas maintain their original quality. This local differentiation allows the system to protect privacy where needed while maintaining overall communication quality in non-sensitive regions.
2Object-affected harmful factors
If object detection and filtering is applied to video content, then privacy is improved, but processing time and complexity increase
Solution Approach 1:
The system performs object detection and classification on video frames as they are captured, before full transmission occurs. By identifying sensitive objects in advance and applying obscuration or removal operations during the encoding process, the system integrates privacy protection into the existing video processing pipeline without requiring separate post-processing steps, thereby managing complexity efficiently.
Solution Approach 2:
The system introduces an intermediary object detection and classification module between the video capture and transmission stages. This intermediary component analyzes video content, identifies sensitive objects, and generates control signals for selective obscuration or removal. By positioning this functionality as an intermediary layer, the system adds privacy protection capability while maintaining a modular architecture that manages processing complexity.
3Adaptability or versatility
If configuration settings are customized for different users and contexts, then communication experience is improved, but system complexity increases
Solution Approach 1:
The system implements a universal configuration framework that handles multiple user preferences, contexts, and sensitivity levels through a single integrated architecture. The object detection, classification, and filtering mechanisms work consistently across different users and scenarios, with configuration parameters that can be adjusted without changing the underlying system structure. This universal design provides customized communication experiences while avoiding the complexity of multiple separate systems.
Data Source
AI summary
A processing system having at least one processor may establish a communication session between a first communication system of a first user and a second communication system of a second user, the communication session including first video content of a first physical environment of the first user and second video content of a second physical environment of the second user, determine a first visualization action for a first physical object in the first physical environment in accordance with a first configuration setting of the first user for the communication session, obtain the first video content from a first camera of the first communication system, detect the first physical object in the first video content, and perform the first visualization action to modify the first video content. The processing system may then transmit first visualization information including the first video content that is modified to the second communication system.